2 citations · 3 across the 2 of their papers we have counts for
3 papers · 1 filter
Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems
Arne Gevaert, Jonathan Peck, Yvan Saeys
Deep Reinforcement Learning uses a deep neural network to encode a policy, which achieves very good performance in a wide range of applications but is widely regarded as a black bo…
Regional Image Perturbation Reduces Norms of Adversarial Examples While Maintaining Model-to-model Transferability
Utku Ozbulak, Jonathan Peck, Wesley De Neve +3
Regional adversarial attacks often rely on complicated methods for generating adversarial perturbations, making it hard to compare their efficacy against well-known attacks. In thi…
CharBot: A Simple and Effective Method for Evading DGA Classifiers
Jonathan Peck, Claire Nie, Raaghavi Sivaguru +5
Domain generation algorithms (DGAs) are commonly leveraged by malware to create lists of domain names which can be used for command and control (C&C) purposes. Approaches based on…